analytic data

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Published By: ZirMed     Published Date: Mar 18, 2015
Welcome to the world of prescriptive analytics—the data science that goes one step beyond predictive.
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ZirMed
Published By: RMS     Published Date: Jul 18, 2019
The more holistic view of risk a property underwriter can get, the better decisions they are likely to make. In order to build up a detailed picture of risk at an individual location, underwriters or agents at coverholders have, until now, had to request exposure analytics on single risks from their portfolio managers and brokers. Also, they had to gather supplementary risk data from a range of external resources, whether it is from Catastrophe Risk Evaluation and Standardizing Target Accumulations (CRESTA) zones to look-ups on Google Maps.
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RMS
Published By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
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aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state, governmental, decisions, data management
    
Aberdeen
Published By: Pure Storage     Published Date: Sep 13, 2019
Discover how to revolutionize processing performance, data intelligence, customer experiences, and GRC. The future of financial services will belong to those who can capture and capitalize on data. And it all begins with employing modern data strategies in four critical areas. Description You’ll learn how to: Leverage AI, machine learning and predictive analytics. Get scalable, high-speed access to vast amounts of data. Respond faster, become more competitive, and attract new customers.
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Pure Storage
Published By: TIBCO Software     Published Date: Jul 22, 2019
What if you could use just one platform to detect all types of major financial crimes? One platform to handle the analytical tasks of fraud detection, including: Data processing and aggregation Data visualization Statistical/mathematical/machine learning modeling Batch/real-time scoring One platform that could successfully reduce complex and time-consuming fraud investigations by combining extremely different domains of knowledge including Business, Economics, Finance, and Law. A platform that can cover payments, credit card transactions, and know your customer (KYC) processes, as well as similar use cases like anti-money laundering (AML), trade surveillance, and crimes such as insurance claims fraud. Learn more about TIBCO's comprehensive software capabilities behind tackling all these types of fraud in this in depth whitepaper.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
AA Ireland specializes in home, motor, and travel insurance and provides emergency rescue for people in their homes and on the road, attending to over 140,000 car break downs every year, 80% of which are fixed on-the-spot. “In each of the last five years, the industry lost a quarter billion in motor insurance," says Colm Carey, chief analytics officer. "So, there's a huge push for new data, models, ways to segment and pick profitable customer types—and get a lot more sophisticated. Our goal is to optimize pricing, understand the types of customers we're bringing, and the types we're trying to attract. We would like to tie that across the business. Marketing will run a campaign, trying to attract a lot of customers, but maybe they're not the right type. "We wanted to step away from industry standard software and go with something that was powerful and future-proof. In 2016, we had an opportunity to analyze all software. We chose the TIBCO® System of Insight with TIBCO BusinessWorks™ i
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TIBCO Software
Published By: TIBCO Software     Published Date: Aug 02, 2019
Fraud is one of the biggest overheads for most financial firms. Detecting crime is hard as fraud constantly evolves and the tools have to be able to evolve with it. Also one of the key areas of focus for most firms is to address the cost of handling the false positives that all automated systems generate. Watch this short demonstration to learn how TIBCO’s advanced analytics and data science solutions can help you overcome these challenges.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
Today, you can improve product quality and gain better control of the entire manufacturing chain with data virtualization, machine learning, and advanced data analytics. With all relevant data aggregated, analyzed, and acted on, sensors, devices, people, and processes become part of a connected Smart Factory ecosystem providing: •? Increased uptime, reduced downtime •? Minimized surplus and defects •? Better yields •? Reduced cost due to better quality •? Fewer deviations and less non-conformance
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
Global producer of polycrystalline silicon for semiconductors, Hemlock Semiconductor needed to accelerate process optimization and eliminate cost. With TIBCO® Connected Intelligence, Hemlock achieved centralized, self-service, governed analysis; revenue gains; cost savings; and more. Fueled by double-digit growth in the markets it serves, Hemlock Semiconductor is adapting to the increasing commoditization within the polysilicon industry and better positioning itself to compete. A key factor in this plan is to equip process-knowledgeable personnel with the skills and tools to accelerate delivery of process optimizations and associated cost elimination. Hemlock turned to a TIBCO® Connected Intelligence solution to address the challenges. By implementing TIBCO Spotfire® and TIBCO® Streaming analytics, TIBCO® Data Science, and TIBCO® Data Virtualization, the company created more self-service analytics. Adding TIBCO BusinessWorks™ integration let the company realize the vision of connect
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TIBCO Software
Published By: Workday APAC     Published Date: Oct 07, 2019
"Considering switching to a single system for finance, planning, and analytics? These leading insurance companies did just that—and they achieved amazing results. This infographic shows how Workday helped them stay competitive, deliver a customer experience like no other, and ensure compliance as well as: Save $400,000 annually with better transactional control Reduce time spent on manual processes, such as quarterly reports Spend more time analyzing data than gathering it "
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Workday APAC
Published By: Group M_IBM Q4'19     Published Date: Sep 26, 2019
IBM has been named a Leader in Gartner's Magic Quadrant for Data & Analytics Services. According to the report, by 2022, 90% of corporate strategies are expected to view information as a critical enterprise asset, and analytics as an essential competency. Data and analytics service providers can help leaders accelerate and transform their ability to deliver data-driven insights and innovation solutions to businesses. Get complimentary access to Gartner's latest Magic Quadrant report for Data & Analytics Service Providers.
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Group M_IBM Q4'19
Published By: Infinidat EMEA     Published Date: May 14, 2019
Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.
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Infinidat EMEA
Published By: Infinidat EMEA     Published Date: Oct 10, 2019
I Big Data e gli analytics workloads sono la nuova frontiera per le aziende. I dati vengono raccolti da fonti che non esistevano 10 anni fa. Tutti i dati dei telefoni cellulari, i dati generati dalle macchine e i dati relativi all’interazione con i siti vengono raccolti e analizzati. Inoltre, con i budget IT sempre più sotto pressione, l’impatto ambientale dei Big Data non fa che aumentare e pone grandi sfi de per i sistemi storage. Questo documento fornisce informazioni sulle problematiche che le applicazioni dei Big Data pongono sullo storage e su come scegliere le più corrette infrastrutture per ottimizzare e consolidare le applicazioni dei Big Data e degli analytics, senza prosciugare le fi nanze.
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Infinidat EMEA
Published By: SAS     Published Date: Sep 05, 2019
Organizations are charging ahead with investments in cloud and analytics to deliver agility, scalability and cost savings. With computing power advancements and continuous growth of data, cloud provides the elastic workloads and flexibility required for modern business. However, the environment of flexibility and choice that cloud provides also creates complexity and challenges. In this white paper, learn how organizations are applying expertise and using the latest methods to move analytics to the cloud, including: • Why are organizations moving analytic work to the cloud? • What are the key challenges and misconceptions? • How do IT leaders provide choice while maintaining control?
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SAS
Published By: SAS     Published Date: Sep 05, 2019
Envision this situation at a growing bank. Its competitive landscape demands an agile response to evolving customer needs. Fortunately, analytically minded professionals in different divisions are seeing results that positively affect the bottom line. • A data scientist in the business development team analyzes data to create customized • experiences for premium customers. • A digital marketer tracks and influences the customer journey for prospective • mortgage customers. • A risk analyst builds risk models for the bank’s loan portfolios. • A data analyst examines data about local customers. • A technical architect defines a new system to protect bank data from internal and • external cyberthreats. • An application developer builds a new mobile app for online customer portfolio • management. Between them, these employees might be using more than a dozen packages for analytics and data management.
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SAS
Published By: TIBCO Software     Published Date: Aug 20, 2019
TIBCO Data Virtualization is a proven approach used by four of the top five integrated energy companies to deliver more analytic data sooner from across upstream and downstream operations. Specific use cases described include: •? Offshore Platform Data Analytics •? Well Maintenance and Repair •? Cross Refinery Web Data Services •? SAP Master Data Quality If you are an energy company facing similar data and analytic challenges, consider TIBCO Data Virtualization.
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data virtualization, analytic data, oil&gas, improved roi, improved efficiency
    
TIBCO Software
Published By: TIBCO Software     Published Date: Aug 20, 2019
“How will we use all the data from the smart grid?”
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greater efficiency, demand forecasting, advanced analytics, smart meters, predictive analytics, data security
    
TIBCO Software
Published By: Workday     Published Date: Feb 20, 2018
How can you put the power of real-time analytics into the hands of business users? Watch this video to learn about the technologies surrounding self-service analytics and data integration, and how you can use them to lead a data-driven organization.
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Workday
Published By: Genesys     Published Date: Jun 19, 2019
Successfully managing a contact center requires a collaborative, multidisciplinary approach to handle a broad range of operational and tactical tasks. Planning, day-to-day operations and quality management must be seamlessly orchestrated, along with human resources functions like recruitment, learning and development, and employee scheduling. Read this executive brief to learn how to transition to an AI strategy that can take your team – and business results – to the next level. See how you can: Create an AI strategy with a single data model that includes routing, interaction analytics, forecasting/scheduling and predictive engagement Harness the power of your data to align customers with the best resource Drive employee effectiveness by ensuring you hire the right people and manage their performance to drive their success over the long term
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Genesys
Published By: Adobe     Published Date: Sep 23, 2019
Like the oxygen we breathe, journey analytics brings life to the customer behind those devices, over time getting to know their favorite pastry choice, when they’re most likely to buy gas, and how long they stay online while in the station’s café. WHY SHOULD THE TARGET AUDIENCE CARE? Business struggle to gain a holistic customer view — the skills to identify actionable insights from multichannel data are in short supply. If they could gain a holistic view of customer attributes and behaviors, they could make sure they get the right content at the right time. SUPPORTING CONCEPTS If you want your customers to enjoy seamless, personalized experiences, you need to treat them like people. That means marketing to the person — not the device. When you know a customer’s interests, wants, and needs — perhaps even before they do — you’ve succeeded at becoming a true experience business. For some, this may require a shift from analytics as a tool to analytics as a way of life. It may also m
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Adobe
Published By: Simba by Magnitude     Published Date: Jul 12, 2019
Today’s C-level executives expect data and analytics to provide them with speed and agility to deliver competitive advantage and to disrupt new markets. But, in today’s complex data environment exists a near paradox between these expectations, that companies will be able to rapidly deliver value using data and analytics--and the complexities of the data landscape, making it more difficult to find, govern, connect to and access the data needed to deliver that value. Once thing is clear: if management expectation is to be met, simplifying connectivity is a must.In this white paper, veteran analyst Mike Ferguson, Managing Director of Intelligent Business Strategies explores how simplifying data access –connectivity –aligns expectations with data realities thus decreasing time to value.
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Simba by Magnitude
Published By: SAP     Published Date: Jun 18, 2011
To stay ahead of the competition in a global marketplace, firms are increasingly speeding up operations, in many cases adopting real-time systems and tools to allow for instant decision-making and faster business cycles. Download here to learn how.
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real-time business analytics, faster decision making, business automation, business metrics, analytical data, sap
    
SAP
Published By: Gigaom     Published Date: Oct 15, 2019
Data pipelines are a reality for most organizations. While we work hard to bring compute to the data, to virtualize and to federate, sometimes data has to move to an optimized platform. While schema-on-read has its advantages for exploratory analytics, pipeline-driven schema-on-write is a reality for production data warehouses, data lakes and other BI repositories. But data pipelines can be operationally brittle, and automation approaches to date have led to a generation of unsophisticated code and triggers whose management and maintenance, especially at-scale, is no easier than the manually-crafted stuff. But it doesn’t have to be that way. With advances in machine learning and the industry’s decades of experience with pipeline development and orchestration, we can take pipeline automation into the realm of intelligent systems. The implications are significant, leading to data-driven agility while eliminating denial of data pipelines’ utility and necessity. To learn more, join us fo
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Gigaom
Published By: SAP     Published Date: Feb 03, 2017
The spatial analytics features of the SAP HANA platform can help you supercharge your business with location-specific data. By analyzing geospatial information, much of which is already present in your enterprise data, SAP HANA helps you pinpoint events, resolve boundaries locate customers and visualize routing. Spatial processing functionality is standard with your full-use SAP HANA licenses.
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SAP
Published By: SAP     Published Date: Mar 09, 2017
There’s strong evidence organizations are challenged by the opportunities presented by external information sources such as social media, government trend data, and sensor data from the Internet of Things (IoT). No longer content to use internal databases alone, they see big data resources augmented with external information resources as what they need in order to bring about meaningful change. According to a September 2015 global survey of 251 respondents conducted by Harvard Business Review Analytic Services, 78 percent of organizations agree or strongly agree that within two years the use of externally generated big data will be “transformational.” But there’s work to be done, since only 21 percent of respondents strongly agree that external data has already had a transformational effect on their firms.
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SAP
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